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Probabilistic Programming Semantics for Name Generation

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 نشر من قبل Michael Wolman
 تاريخ النشر 2020
  مجال البحث الهندسة المعلوماتية
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We make a formal analogy between random sampling and fresh name generation. We show that quasi-Borel spaces, a model for probabilistic programming, can soundly interpret Starks $ u$-calculus, a calculus for name generation. Moreover, we prove that this semantics is fully abstract up to first-order types. This is surprising for an off-the-shelf model, and requires a novel analysis of probability distributions on function spaces. Our tools are diverse and include descriptive set theory and normal forms for the $ u$-calculus.

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